Bayesian estimation of generalized partition of unity copulas
Dependence Modeling, 2020 This paper proposes a Bayesian estimation algorithm to estimate Generalized Partition of Unity Copulas (GPUC), a class of nonparametric copulas recently introduced by [18].
Masuhr Andreas, Trede Mark
doaj +1 more source
Identification and Estimation of Intensive Margin Effects by Difference-in-Difference Methods
Journal of Causal Inference, 2020 This paper discusses identification and estimation of causal intensive margin effects. The causal intensive margin effect is defined as the treatment effect on the outcome of individuals with a positive outcome irrespective of whether they are treated or
Hersche Markus, Moor Elias
doaj +1 more source
Nonparametric volatility density estimation for discrete time models [PDF]
, 2002 We consider discrete time models for asset prices with a stationary volatility process. We aim at estimating the multivariate density of this process at a set of consecutive time instants.
Spreij, Peter +2 more
core +4 more sources
Orthogonal Polynomials for Seminonparametric Instrumental Variables Model [PDF]
, 2014 We develop an approach that resolves a {\it polynomial basis problem} for a class of models with discrete endogenous covariate, and for a class of econometric models considered in the work of Newey and Powell (2003), where the endogenous covariate is ...
Kovchegov, Yevgeniy, Yildiz, Nese
core +3 more sources
Volatility filtering in estimation of kurtosis (and variance)
Dependence Modeling, 2019 The kurtosis of the distribution of financial returns characterized by high volatility persistence and thick tails is notoriously difficult to estimate precisely.
Anatolyev Stanislav
doaj +1 more source
Prediction of time series by statistical learning: general losses and fast rates
Dependence Modeling, 2013 We establish rates of convergences in statistical learning for time series forecasting. Using the PAC-Bayesian approach, slow rates of convergence √ d/n for the Gibbs estimator under the absolute loss were given in a previous work [7], where n is the ...
Alquier Pierre +2 more
doaj +1 more source
Functional generalized autoregressive conditional heteroskedasticity [PDF]
, 2015 Heteroskedasticity is a common feature of financial time series and is commonly addressed in the model building process through the use of ARCH and GARCH processes. More recently multivariate variants of these processes have been in the focus of research
Aue, Alexander +2 more
core +2 more sources
Auto-tail dependence coefficients for stationary solutions of linear stochastic recurrence equations and for GARCH(1,1) [PDF]
, 2010 We examine the auto-dependence structure of strictly stationary solutions of linear stochastic recurrence equations and of strictly stationary GARCH(1, 1) processes from the point of view of ordinary and generalized tail dependence coefficients.
B Basrak +6 more
core +1 more source
The role of Skorokhod space in the development of the econometric analysis of time series [PDF]
, 2008 This paper discusses the fundamental role played by Skorokhod space, through its underpinning of functional central limit theory, in the development of the paradigm of unit roots and co-integration.
Mc CRORIE, J. Roderick
core +2 more sources
Locally adaptive estimation methods with application to univariate time series [PDF]
, 2008 The paper offers a unified approach to the study of three locally adaptive estimation methods in the context of univariate time series from both theoretical and empirical points of view. A general procedure for the computation of critical values is given.
Elagin, Mstislav
core +3 more sources